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Competitive Distributed File Allocation
, 1993
"... This paper deals with the file allocation problem [BFR92] concerning the dynamic optimization of communication costs to access data in a distributed environment. We develop a dynamic file reallocation strategy that adapts online to a sequence of read and write requests whose location and relative ..."
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Cited by 106 (12 self)
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This paper deals with the file allocation problem [BFR92] concerning the dynamic optimization of communication costs to access data in a distributed environment. We develop a dynamic file reallocation strategy that adapts online to a sequence of read and write requests whose location and relative frequencies are completely unpredictable. This is achieved by replicating the file in response to read requests and migrating the file in response to write requests while paying the associated communications costs, so as to be closer to processors that access it frequently. We develop first explicit deterministic online strategy assuming existence of global information about the state of the network; previous (deterministic) solutions were complicated and more expensive. Our solution has (optimal) logarithmic competitive ratio. The paper also contains the first explicit deterministic data migration [BS89] algorithm achieving the best known competitive ratio for this problem. Using somewhat ...
Competitive Algorithms for Distributed Data Management
 In Proceedings of the 24th Annual ACM Symposium on Theory of Computing
"... We deal with the competitive analysis of algorithms for managing data in a distributed environment. We deal with the file allocation problem ([DF], [ML]), where copies of a file may be be stored in the local storage of some subset of processors. Copies may be replicated and discarded over time so ..."
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Cited by 100 (8 self)
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We deal with the competitive analysis of algorithms for managing data in a distributed environment. We deal with the file allocation problem ([DF], [ML]), where copies of a file may be be stored in the local storage of some subset of processors. Copies may be replicated and discarded over time so as to optimize communication costs, but multiple copies must be kept consistent and at least one copy must be stored somewhere in the network at all times. We deal with competitive algorithms for minimizing communication costs, over arbitrary sequences of reads and writes, and arbitrary network topologies. We define the constrained file allocation problem to be the solution of many individual file allocation problems simultaneously, subject to the constraints of local memory size. We give competitive algorithms for this problem on the uniform network topology. We then introduce distributed competitive algorithms for online data tracking (a generalization of mobile user tracking [AP1...
Distributed Paging for General Networks
, 1996
"... Distributed paging [BFR92, ABF93b, AK95] deals with the dynamic allocation of copies of files in a distributed network as to minimize the total communication cost over a sequence of read and write requests. Most previous work deals with the file allocation problem [BS89, West91, CLRW93, ABF93a, ..."
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Cited by 58 (5 self)
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Distributed paging [BFR92, ABF93b, AK95] deals with the dynamic allocation of copies of files in a distributed network as to minimize the total communication cost over a sequence of read and write requests. Most previous work deals with the file allocation problem [BS89, West91, CLRW93, ABF93a, WY93, Koga93, AK94, LRWY94] where infinite nodal memory capacity is assumed. In contrast the distributed paging problem makes the more realistic assumption that nodal memory capacity is limited. Former work on distributed paging deals with the problem only in the case of a uniform network topology. This paper gives the first distributed paging algorithm for general networks. The algorithm is competitive in storage and communication. The competitive ratios are polylogarithmic in the total number of network nodes and the diameter of the network. Johns Hopkins University and Lab. for Computer Science, MIT. Supported by Air Force Contract TNDGAFOSR860078, ARO contract DAAL0386K0171, NSF contract 9114440CCR, DARPA contract N00014J 921799, and a special grant from IBM. EMail: baruch@theory.lcs.mit.edu. y Department of Computer Science, School of Mathematics, TelAviv University, TelAviv 69978, Israel. Supported by a grant from the Israeli Academy of Sciences. Email: yairb@math.tau.ac.il, fiat@math.tau.ac.il 0 1
Randomized Competitive Algorithms for the List Update Problem
 Algorithmica
, 1992
"... We prove upper and lower bounds on the competitiveness of randomized algorithms for the list update problem of Sleator and Tarjan. We give a simple and elegant randomized algorithm that is more competitive than the best previous randomized algorithm due to Irani. Our algorithm uses randomness only d ..."
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Cited by 39 (2 self)
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We prove upper and lower bounds on the competitiveness of randomized algorithms for the list update problem of Sleator and Tarjan. We give a simple and elegant randomized algorithm that is more competitive than the best previous randomized algorithm due to Irani. Our algorithm uses randomness only during an initialization phase, and from then on runs completely deterministically. It is the first randomized competitive algorithm with this property to beat the deterministic lower bound. We generalize our approach to a model in which access costs are fixed but update costs are scaled by an arbitrary constant d. We prove lower bounds for deterministic list update algorithms and for randomized algorithms against oblivious and adaptive online adversaries. In particular, we show that for this problem adaptive online and adaptive offline adversaries are equally powerful. 1 Introduction Recently much attention has been given to competitive analysis of online algorithms [7, 20, 22, 25]. Ro...
On Page Migration and Other Relaxed Task Systems
, 1997
"... This paper is concerned with the page migration (or file migration) problem [BS89] as part of a large class of online problems. The page migration problem deals with the management of pages residing in a network of processors. In the classical problem there is only one copy of each page which is ..."
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Cited by 28 (4 self)
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This paper is concerned with the page migration (or file migration) problem [BS89] as part of a large class of online problems. The page migration problem deals with the management of pages residing in a network of processors. In the classical problem there is only one copy of each page which is accessed by different processors over time. The page is allowed to be migrated between processors. However a migration incurs higher communication cost than an access (proportionally to the page size). The problem is that of deciding when and where to migrate the page in order to lower access costs. A more general setting is the kpage migration where we wish to maintain k copies of the page. The page migration problems are concerned with a dilemma common to many online problems: determining when is it beneficial to make configuration changes. We deal with the relaxed task systems model which captures a large class of problems of this type, that can be described as the generalizati...
Distributed Paging
 The 1996 Dagstuhl Workshop on Online Algorithms
, 1996
"... . We survey distributed data management problems including distributed paging, file allocation, and file migration. 1 Introduction Many modern information services know no national boundaries. The widespread use of the Internet and Internetrelated applications such as the World Wide Web is growi ..."
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Cited by 14 (0 self)
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. We survey distributed data management problems including distributed paging, file allocation, and file migration. 1 Introduction Many modern information services know no national boundaries. The widespread use of the Internet and Internetrelated applications such as the World Wide Web is growing fantastically on an annual basis. This survey deals with distributed data management problems. Such problems may arise as a memorymanagement problem for a globally addressed shared memory in a multiprocessor system as well as in a distributed network of processors where data files are kept in different sites and may be accessed for information retrieval by dispersed users and applications. In this context, a file may be a conventional single file, a system database, fragments of a database, or any combination of these. When a processor wishes to access a file it must send a request to a processor holding the file and the desired information is transmitted back. The communication cost in...
Competitive Access Time via Dynamic Storage Rearrangement
, 1995
"... We deal with a natural generalization of one of the seminal problems in the study of online computation, list management [ST85a, IRSW91, Irani91]. We consider a doubly linked list with a pointer pointing to the last item accessed. Our goal, as with list management, is to minimize the total number o ..."
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Cited by 4 (0 self)
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We deal with a natural generalization of one of the seminal problems in the study of online computation, list management [ST85a, IRSW91, Irani91]. We consider a doubly linked list with a pointer pointing to the last item accessed. Our goal, as with list management, is to minimize the total number of pointers traversed over a sequence of searches. This problem models issues of dynamic adaptive disk optimization. In this work we initiate the study of this problem in the competitive setting. Our main result is showing nontrivial upper bounds on the competitive ratio. For restricted access patterns we give algorithms that have much better competitive ratios. To complement those bounds we show that there is no constantcompetitive algorithm for the problem with arbitrary access patterns, even against an adversary that does not rearrange its items. Department of Computer Science, Tel Aviv University, Tel Aviv. Research supported in part by a grant from the Israel Academy of Sciences. EM...
Competitive Distributed File Allocation (Extended Abstract)
"... ) Baruch Awerbuch Yair Bartal y Amos Fiat y Abstract This paper deals with the file allocation problem [BFR92] concerning the dynamic optimization of communication costs to access data in a distributed environment. We develop a dynamic file reallocation strategy that adapts online to a sequen ..."
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) Baruch Awerbuch Yair Bartal y Amos Fiat y Abstract This paper deals with the file allocation problem [BFR92] concerning the dynamic optimization of communication costs to access data in a distributed environment. We develop a dynamic file reallocation strategy that adapts online to a sequence of read and write requests whose location and relative frequencies are completely unpredictable. This is achieved by replicating the file in response to read requests and migrating the file in response to write requests while paying the associated communications costs, so as to be closer to processors that access it frequently. We develop first explicit deterministic online strategy assuming existence of global information about the state of the network; previous (deterministic) solutions were nonconstructive and more expensive. Our solution has (optimal) logarithmic competitive factor. The paper also contains the first explicit deterministic data migration [BS89] algorithm achieving the ...
.1 Page Migration
"... distributed paging have been defined by Bartal, Fiat and Rabani [BFR92]. 10.1.1 A 3competitive Randomized Algorithm The intuitive idea here is that we need about D requests in a region before we can decide that it is worthwhile to move the page to that region. Hence, for any one request, we move ..."
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distributed paging have been defined by Bartal, Fiat and Rabani [BFR92]. 10.1.1 A 3competitive Randomized Algorithm The intuitive idea here is that we need about D requests in a region before we can decide that it is worthwhile to move the page to that region. Hence, for any one request, we move the page with probability about 1=D. More precisely, when the page is at s and the request is at r, the FLIP algorithm first serves the request, and then moves the page from s to r with probability 1 2D . This algorithm is due to Westbrook [West91]. Claim 10.1 FLIP is 3competitive against adaptive online adversaries. Proof: We define the potential function \Phi = 3D \Delta d(t; s); 101 102 Lecture 10: February 20 whe